Non-linear feedback processes and a latitudinal gradient in the climatic effects determine green spruce aphid outbreaks in the UK

The role of climatic fluctuations in determining the dynamics of insect populations has been a classical problem in population ecology. Here, we use long-term annual data on green spruce aphid populations at nine localities in the UK for determining the importance of endogenous processes, local weather and large-scale climatic factors. We rely on diagnostic and modelling tools from population dynamic theory to analyse these long-term data and to determine the role of the North Atlantic Oscillation (NAO) and local weather as exogenous factors influencing aphid dynamics. Our modelling suggests that the key elements determining population fluctuations in green spruce aphid populations in the UK are the strong non-linear feedback structure, the high potential for population growth and the effects of winter and spring weather. The results indicate that the main effect of the NAO on green spruce aphid populations is operating through the effect of winter temperatures on the maximum per capita growth rate (R_m). In particular, we can predict quite accurately the occurrence of an outbreak by using a simple logistic model with weather as a perturbation effect. However, model predictions using different climatic variables showed a clear geographical signature. The NAO and winter temperature were best for predicting observed dynamics toward the southern localities, while spring temperature was a much better predictor of aphid dynamics at northern localities. Although aphid species are characterized by complex life-cycles, we emphasize the value of simple and general population dynamic models in predicting their dynamics.     

Analysis of phenotypic change in relation to climatic drivers in a population of Soay sheep Ovis aries

Climatic change has frequently been identified as a key driver of change in biological communities. These changes can take the form of alterations to population dynamics, phenotypic characters, genetics and the life history of organisms and can have impacts on entire ecosystems. This study presents a novel investigation of how changes in a large scale climatic index, the North Atlantic Oscillation (NAO) can influence population dynamics and phenotypic characters in a population of ungulates. We use an integral projection model combined with actual climate change predictions to project future body size distributions for a population of Soay sheep Ovis aries. The climate change predictions used to direct our model projections were taken from published results of climate models, covering a range of different emissions scenarios. Our model results showed that for positive changes in the mean NAO large population declines occurred simultaneously with increases in mean body weight. The exact direction and magnitude of changes to population dynamics and character distributions were dependent on the greenhouse gas emissions scenario and model used to predict the NAO. This study has demonstrated how integral projection models can use outputs of climate models to direct projections of population dynamics and phenotypic character distributions. This approach allows the results of this study to be placed within current climate change research. The nature of integral projection models means that this methodology can be easily applied to other populations. The model can also be easily updated when new climate change predictions become available, making it a useful tool for understanding potential population level responses to climatic change. Synthesis Understanding how changes in climate affect biological communities is a key component in predicting the future form of populations. Utilising a novel approach that incorporates climatic drivers (in this instance the winter North Atlantic Oscillation) into an integral projection model framework, we predict future Soay sheep dynamics under specific climate change scenarios. Tracking quantitative trait distributions and life history metrics, our results predict declining population size and increasing body weight for an increasingly positive winter North Atlantic Oscillation index, as predicted by climate models. This has important implications for future wildlife management strategies and linking demographic responses to climate change.     

Modelling non-additive and nonlinear signals from climatic noise in ecological time series: Soay sheep as an example

Understanding how climate can interact with other factors in determining patterns of species abundance is a persistent challenge in ecology. Recent research has suggested that the dynamics exhibited by some populations may be a non-additive function of climate, with climate affecting population growth more strongly at high density than at low density. However, we lack methodologies to adequately explain patterns in population growth generated as a result of interactions between intrinsic factors and extrinsic climatic variation in non-linear systems. We present a novel method (the Functional Coefficient Threshold Auto-Regressive (FCTAR) method) that can identify interacting influences of climate and density on population dynamics from time-series data. We demonstrate its use on count data on the size of the Soay sheep population, which is known to exhibit dynamics generated by nonlinear and non-additive interactions between density and climate, living on Hirta in the St Kilda archipelago. The FCTAR method suggests that climate fluctuations can drive the Soay sheep population between different dynamical regimes--from stable population size through limit cycles and non-periodic fluctuations.     

Cumulative weather effects can impact across the whole life cycle

Predicting how species will be affected by future climatic change requires the underlying environmental drivers to be identified. As vital rates vary over the lifecycle, structured population models derived from statistical environment–demography relationships are often used to inform such predictions. Environmental drivers are typically identified independently for different vital rates and demographic classes. However, these rates often exhibit positive temporal covariance, suggesting that vital rates respond to common environmental drivers. Additionally, models often only incorporate average weather conditions during a single, a priori chosen time window (e.g. monthly means). Mismatches between these windows and the period when the vital rates are sensitive to variation in climate decrease the predictive performance of such approaches. We used a demographic structural equation model (SEM) to demonstrate that a single axis of environmental variation drives the majority of the (co)variation in survival, reproduction, and twinning across six age–sex classes in a Soay sheep population. This axis provides a simple target for the complex task of identifying the drivers of vital rate variation. We used functional linear models (FLMs) to determine the critical windows of three local climatic drivers, allowing the magnitude and direction of the climate effects to differ over time. Previously unidentified lagged climatic effects were detected in this well‐studied population. The FLMs had a better predictive performance than selecting a critical window a priori, but not than a large‐scale climate index. Positive covariance amongst vital rates and temporal variation in the effects of environmental drivers are common, suggesting our SEM–FLM approach is a widely applicable tool for exploring the joint responses of vital rates to environmental change.     

Assessing the relative importance of intrinsic and extrinsic influence on sheep population dynamics on Hirta Island, UK

Identifying the relative importance of intrinsic factors and extrinsic environmental variations on population or ecosystem dynamics is important for ecological conservation research. Here, we use a systematic method proposed by De Menezes and Barabási [2004. Separating internal and external dynamics of complex systems. Physical Review Letters, 93, 068701] to reanalyse the long-term monitoring data of Soay sheep population fluctuations and climate variations on Hirta Island, UK. Our results indicate that the climate conditions have a higher impact than internal factors on the fluctuations of sheep population. The sheep population dynamics are internally self-regulating. The scaling relationships between sheep population and external and internal standard deviations are similar. The threshold of the sheep population on this island as determined by our study is around 1197, which is consistent with previous studies by other methods. Our study indicates that this systematic method may help to understand some of the complicated aspects of population dynamics about which detailed knowledge is limited.     

Large‐scale climatic variability affects the dynamics of tropical skipjack tuna in the Western Pacific Ocean

The role of climate variability in determining the fluctuations of fish populations had been a traditional problem in ecology. In this paper, we studied the role of the Southern Oscillation Index (SO) and the Pacific Decadal Oscillation (PDO) on the population dynamics of the western stock of the skipjack tuna Katsuwonus pelamis. Our analysis was based in three sequential steeps: a diagnostic approach to deduce what kind of population dynamic model should be more appropriate, the modelling of capture per unit of effort data through a logistic model, and the use of population dynamic theory for analyzing the effect of exogenous perturbations. We find that direct and one‐year lagged negative PDO effects and one‐year lagged negative SO effects were needed to explain annual tuna fluctuations. Models including the combined effects of these climatic indexes explain 80% of the variance in tuna fluctuations. In addition, these models provided very accurate predictions of independent skipjack tuna observed dynamics. This result is encouraging because the inherent variability in CPUE data and the not well determined link between climate and ecological processes. Finally, this study demonstrates that simple models can offer reasonable explanations and accurate predictions of tuna fluctuations, provided they are based on a sound theoretical framework.     

Climatic influences on the mortality of sheep during long-distance sea transport

Research on the causes of sheep death in sea voyages from Australia to the Middle East is limited, in particular little is known about the influence of climatic factors. Mortality data from 417 shipments of sheep exported over an 11-year period (November 2004 to June 2015) were modelled retrospectively to determine associated climatic factors. The statistical analysis were performed for both the full data set with 417 voyages based on actual and estimated departure and arrival dates and a restricted data set with 71 voyages based on actual dates. The results of the full data set demonstrated a seasonal mortality pattern, with more deaths occurring on sea voyages leaving Australia in the southern hemisphere winter or spring than those departing in Australian summer or autumn. Heat stress and inadequate fat mobilisation for energy supply when sheep are inappetant on shipments may explain this seasonality. Based on these two models, the voyage and weather factors associated with sheep mortalities included departure year, autumn departure in the southern hemisphere, voyage duration, single or multiple loading port(s), weekly mean dry bulb temperature and wind speed at departure ports, and humidity at destination ports. Significant correlations were observed between weather variables at the departure ports in the Australian winter and a high sheep mortality rate during voyages. This, together with the anticipated increased heat stress risk as a result of climate change, suggests that there could be review of the trade from Australia in the southern hemisphere winter. The influence of weather at the departure ports should be considered in sheep mortality prediction models, especially Australia’s heat stress risk assessment model.     

Main determinants of rodent population fluctuations in managed Central European temperate lowland forests

Whilst studies have shown that climatic (North Atlantic Oscillation (NAO)) and biotic (acorn production) factors influence rodent populations, mechanisms driving temporal and spatial fluctuation of rodent populations are understudied. This study evaluates relationships between the influence of environmental factors (biotic and abiotic) and phenotypic characteristics across two rodent feeding guilds (granivorous and non-granivorous species) represented by four species of rodents in Central Europe. We hypothesise that the relationship between acorn density and population growth rate are indirectly affected by climatic factors (winter NAO) and that these effects differ amongst herbivorous and granivorous species. In addition, we also tested whether effects of weather and competition on individual phenotype characteristic vary amongst mast and non-mast years. Rodent populations were estimated by catching individuals in snap traps during the growing season (from March to November) over a period of 9 years at three sites. The results of the generalised linear model provide evidence that acorn production best explained the population fluctuations. We therefore conclude that the between-year population fluctuations in rodent abundance were governed by density dependence and initiated primarily by acorn mast years. Auto-regressive models also revealed direct density dependence in combination with the direct effects of mast years. Therefore, strong intraspecific competition for food is likely in years following mast years. Our results also showed that abundance of non-granivorous species is mainly influenced by local weather conditions which could regulate food quality and abundance. On the other hand, population dynamics of granivorous species are caused directly by acorn density and indirectly by climatic condition influencing acorn production.     

Combined effect of ENSO and SAM on the population dynamics of the invasive yellowjacket wasp in central Chile

The population dynamics of the yellowjacket wasp (Vespula germanica Fabricus) in central Chile were analyzed for the first time. Using a simple Ricker logistic model and adding the effects of local weather variables (temperature and precipitation) and large-scale climate phenomena as El Niño Southern Oscillation (ENSO) and the Southern Annular Mode (SAM), we modeled the interannual fluctuations in nest density. The best model according to the Bayesian information criterion (BIC) included 1-year-lag negative feedback combined with the positive additive effects of ENSO and SAM. According to this model, yellowjacket nest density was favored by warm and dry winters, which probably influenced the survival of overwintering queens. Large-scale climatic variables [Southern Oscillation Index (SOI) and SAM] described the effect of exogenous factors in wasp fluctuations better than local weather variables did. Our results emphasize the usefulness of climate indices and simple theoretical-based models in insect ecological research.     

A climate index and mule deer fawn survival in Montana

A sign of deviation type of index was used to convert standard temperature and precipitation data into a readily used form for the study of deer population dynamics. Statistically significant correlations between the climate index and mule deer fawn survival were demonstrated for four different mule deer populations in Montana. These correlations led to reasonable biological hypotheses delineating the linkage between climate and fawn survival in each of the four areas. The correlations support the frequent observations in the wildlife literature concerning the importance of summer and winter range. They also suggest that human activities may interact with climate in a manner which affects deer fawn survival. In general, in these areas, fawn survival was favored by relatively warm-moist summer, warm-dry winter and cool-dry hunting season weather. The apparent affect of spring weather was variable. Fawn survival in two areas was enhanced by cool-dry summer weather. This reversed response could be the result of human use of the areas, including livestock grazing. It is concluded that this index of climatic fluctuations can be a versatile and useful tool in assessing the impact of climate upon deer populations. In general, weather can be described as a strong biasing factor even when direct effects cannot be consistently demonstrated.     

Climate mediated exogenous forcing and synchrony in populations of the oak aphid in the UK

Contemporary population dynamics theory suggests that animal fluctuations in nature are the result of the combined forces of intrinsic and exogenous factors. Weather is the iconic example of an exogenous force. The common approach for analyzing the relationship between population size and climatic variables is by simple correlation or using the climate as an additive covariable in statistical models. Here, we evaluated different functional forms in which climatic variables could influence population dynamics of the oak aphid Tuberculatus annulatus both in each locality and in relation to synchrony between localities. Results indicate that in at least four of eight aphid populations, climate influences population dynamics by modifying the carrying capacity of the system (lateral effect mediated by winter precipitation). Additionally, path analysis showed that synchrony in population dynamics is highly correlated with synchrony in winter precipitation regime, and the spatial scale of both processes is similar, which suggests that this is an example of the Moran effect. Our results show the key effects of precipitation on intra and inter population processes of this aphid. The methods used, mixing population dynamics modelling and test of synchrony, allowed us to connect the direct and indirect effects of exogenous variables into each population with patterns of synchrony inter populations.     

Modeling linkage disequilibrium in natural populations: the example of the Soay sheep population of St. Kilda, Scotland

The use of linkage disequilibrium to localize the genes underlying quantitative traits has received considerable attention in the livestock genetics community over the past few years. This has resulted in the investigation of linkage disequilibrium structures of several domestic livestock populations to assess their potential use in fine-mapping efforts. However, the linkage disequilibrium structure of free-living populations has been less well investigated. As the direct evaluation of linkage disequilibrium can be both time consuming and expensive the use of simulations that include as many aspects of population history as possible is advocated as an alternative. A simulation of the linkage disequilibrium structure of the Soay sheep population of St. Kilda, Scotland, is provided as an example. The simulated population showed significant decline of linkage disequilibrium with genetic distance and low levels of background linkage disequilibrium, indicating that the Soay sheep population is a viable resource for linkage disequilibrium fine mapping of quantitative trait loci.     

Effects of climate on population fluctuations of ibex

Predicting the effects of the expected changes in climate on the dynamics of populations require that critical periods for climate‐induced changes in population size are identified. Based on time series analyses of 26 Swiss ibex (Capra ibex) populations, we show that variation in winter climate affected the annual changes in population size of most of the populations after accounting for the effects of density dependence and demographic stochasticity. In addition, precipitation during early summer also influenced the population fluctuations. This suggests that the major influences of climate on ibex population dynamics operated either through loss of individuals during winter or early summer, or through an effect on fecundity. However, spatial covariation in these climate variables was not able to synchronize the population fluctuations of ibex over larger distances, probably due to large spatial heterogeneity in the effects of single climate variables on different populations. Such spatial variation in the influence of the same climate variable on the local population dynamics suggests that predictions of influences of climate change need to account for local differences in population dynamical responses to climatic conditions.     

Demographics in an alpine reindeer herd: effects of density and winter weather

We examined how population density, winter weather, snow conditions, and 2 large-scale climatic indices (North Atlantic Oscillation, NAO, and Arctic Oscillation, AO) influenced demography (reproduction and mortality) in an alpine herd of semi-domesticated reindeer Rangifer tarandus between 1959 and 2000 in Finnish Lapland. The herd lived on heavily grazed lichen pastures, with winter densities between 0.8 and 3.9 individuals km⁻². Icing conditions occurred every 7th yr, on an average, and decreased reproductive rate (calves/females) by 49%. In general linear models icing remarkably increased the fit of snow models to reproductive rate. Incorporation of an interaction term between icing and the snow depth index provided better fit than a model without interaction. Delayed snowmelt decreased reproductive rate. For the day of snowmelt, however, the model without interaction was better than the interaction model. These 3 models provided the best fit to the data and accounted for 51–54% of the variation in reproductive rate. Winter mortality was related to density and large-scale climatic indices, but not to local winter weather except a slight increase in mortality during an icing winter. The best model for winter mortality, including reindeer density and NAO, accounted for 26% of variation in mortality. Three factors may be involved explaining weak density dependence or the lack of such dependence; climate change scenarios that predict higher winter temperature, more frequent thawing-freezing periods, and deeper snow would be expected to decrease reproductive rate and increase winter mortality of reindeer and thus to reduce profitability of reindeer husbandry. In contrast, early springs would be advantageous for reindeer in the short term.     

Heritable variation in resistance to gastro-intestinal nematodes in an unmanaged mammal population.

The impact of parasites on natural populations has received considerable attention from evolutionary biologists in recent years. Central to a number of theoretical developments during this period is the assumption of additive genetic variation in resistance to parasites. However, very few studies have estimated the heritability of parasite resistance under field conditions, and those that have are mainly restricted to birds and their ectoparasites. In this paper, to our knowledge, we show for the first time in a free-ranging mammal population, Soay sheep (Ovis aries) living on the islands of St Kilda, that there is significant heritable variation in resistance to gastrointestinal nematodes. This result is consistent with earlier studies on this population which have indicated locus-specific associations with parasite resistance. We discuss our results in the context of current studies examining heritable resistance to parasites in domestic sheep and the possible mechanisms of selective maintenance of genetic variation for resistance to gastrointestinal nematodes in the St Kilda Soay sheep population.     

Spatial heterogeneity in climate change effects decouples the long‐term dynamics of wild reindeer populations in the high Arctic

The ‘Moran effect’ predicts that dynamics of populations of a species are synchronized over similar distances as their environmental drivers. Strong population synchrony reduces species viability, but spatial heterogeneity in density dependence, the environment, or its ecological responses may decouple dynamics in space, preventing extinctions. How such heterogeneity buffers impacts of global change on large‐scale population dynamics is not well studied. Here, we show that spatially autocorrelated fluctuations in annual winter weather synchronize wild reindeer dynamics across high‐Arctic Svalbard, while, paradoxically, spatial variation in winter climate trends contribute to diverging local population trajectories. Warmer summers have improved the carrying capacity and apparently led to increased total reindeer abundance. However, fluctuations in population size seem mainly driven by negative effects of stochastic winter rain‐on‐snow (ROS) events causing icing, with strongest effects at high densities. Count data for 10 reindeer populations 8–324 km apart suggested that density‐dependent ROS effects contributed to synchrony in population dynamics, mainly through spatially autocorrelated mortality. By comparing one coastal and one ‘continental’ reindeer population over four decades, we show that locally contrasting abundance trends can arise from spatial differences in climate change and responses to weather. The coastal population experienced a larger increase in ROS, and a stronger density‐dependent ROS effect on population growth rates, than the continental population. In contrast, the latter experienced stronger summer warming and showed the strongest positive response to summer temperatures. Accordingly, contrasting net effects of a recent climate regime shift—with increased ROS and harsher winters, yet higher summer temperatures and improved carrying capacity—led to negative and positive abundance trends in the coastal and continental population respectively. Thus, synchronized population fluctuations by climatic drivers can be buffered by spatial heterogeneity in the same drivers, as well as in the ecological responses, averaging out climate change effects at larger spatial scales.     

Examination of a region showing linkage map discrepancies across sheep breeds

The availability of accurate linkage maps is an important step for the localization of genetic variants of interest. However, most studies in livestock assume the published map is applicable in their population despite the large differences between the breeds of a species. A region of sheep Chromosome 1 was previously identified as providing evidence for a marker order inconsistent with the published linkage map. In this study the identified region was investigated in more detail. Four microsatellite markers covering the central 5 cM of the inconsistent region and two flanking markers were genotyped in three sheep breeds, a commercial population (Charollais), an experimental population (Scottish Blackface), and a feral population (Soay). With the inclusion of the published linkage map, this provided evidence for three different marker orders across four sheep populations. Evidence for selection in this region was investigated using both a single-point allelic competition model and a multipoint allele-sharing statistic. Only the Charollais population provided evidence for selection, with significant transmission bias observed at marker BM7145. The implications of variation in linkage maps on the design and analysis of fine-mapping studies are discussed.     

The relative roles of density and climatic variation on population dynamics and fecundity rates in three contrasting ungulate species

The relative influences of density-dependent and -independent processes on vital rates and population dynamics have been debated in ecology for over half a century, yet it is only recently that both processes have been shown to operate within the same population. However, generalizations on the role of each process across species are rare. Using a process-orientated generalized linear modelling approach we show that variations in fecundity rates in populations of three species of ungulates with contrasting life histories are associated with density and winter weather in a remarkably similar manner. However, there are differences and we speculate that they are a result of differences in size between the species. Much previous research exploring the association between vital rates, population dynamics and density-dependent and -independent processes has used pattern-orientated approaches to decompose time-series into contributions from density-dependent and -independent processes. Results from these analyses are sometimes used to infer associations between vital rates, density and climatic variables. We compare results from pattern-orientated analyses of time-series with process-orientated analyses and report that the two approaches give different results. The approach of analysing relationships between vital rates, density and climatic variables may detect important processes influencing population dynamics that time-series methodologies may overlook.     

Extrapolation methods for climate time series revisited – Spatial correlations in climatic fluctuations influence simulated tree species abundance and migration

Simulations of tree population dynamics under past and future climatic changes with time- and space-discrete models often suffer from a lack of detailed long-term climate time series that are required to drive these models. Inter- and extrapolation methods which are applied to generate long-term series differ in terms of whether they do or do not account for spatial correlation of climatic fluctuations. In this study we compared tree species abundance and migration outcomes from simulations using extrapolation methods generating spatially correlated (SC) and spatially independent (SI) climatic fluctuations. We used the spatially explicit and linked forest-landscape model TreeMig and a simple cellular automaton to demonstrate that spatial correlation of climatic fluctuations affects simulation outcomes. We conclude that methods to generate long-term climate time series should account for the spatial correlation of climatic fluctuations found in available climate records when simulating tree species abundance and migration.     

No evidence for major histocompatibility complex-dependent mating patterns in a free-living ruminant population.

Conventionally, the extraordinary diversity of the vertebrate major histocompatibility complex (MHC is thought to have evolved in response to parasites and pathogens affecting fitness. More recently, reproductive mechanisms such as disassortative mating have been suggested as alternative mechanisms maintaining MHC diversity. A large unmanaged population of Soay sheep (Ovis aries L.) was used to investigate reproductive mechanisms in the maintenance of MHC diversity. Animals were sampled as new-born lambs and between 887 and 1209 individuals were typed at each of five microsatellite markers located either within or flanking the ovine MHC. All loci were in Hardy-Weinberg proportions. A novel likelihood-based approach was developed to analyse mating patterns using paternity data. No evidence for non-random mating with respect to MHC markers was found using this technique. We conclude that MHC diversity in the St Kildan Soay sheep population is unlikely to be maintained by mating preferences and that, in contrast with evidence from experimental mice populations, MHC variation plays no role in the mating structure of this population.